MINIMIZING MANUFACTURING AND QUALITY COSTS IN MULTIRESPONSE OPTIMIZATION

Determination of the best operational settings for products or processes is usually accomplished through single-objective-function optimization routines, but in order to select the best design and operating control factors, all measures of quality must ..

[1]  James M. Lucas,et al.  How to Achieve a Robust Process Using Response Surface Methodology , 1994 .

[2]  A. Harvey Estimating Regression Models with Multiplicative Heteroscedasticity , 1976 .

[3]  G. Derringer,et al.  Simultaneous Optimization of Several Response Variables , 1980 .

[4]  A. Khuri,et al.  Simultaneous Optimization of Multiple Responses Represented by Polynomial Regression Functions , 1981 .

[5]  Susan L. Albin,et al.  VARIANCE OF PREDICTED RESPONSE AS AN OPTIMIZATION CRITERION IN MULTIRESPONSE EXPERIMENTS , 2000 .

[6]  A. C. Shoemaker,et al.  Performance Measures Independent of Adjustment: An Explanation and Extension of Taguchi's Signal-to-Noise Ratios , 1987 .

[7]  Margaret J. Robertson,et al.  Design and Analysis of Experiments , 2006, Handbook of statistics.

[8]  Derek J. Pike,et al.  Empirical Model‐building and Response Surfaces. , 1988 .

[9]  Enrique Del Castillo,et al.  Multiresponse Process Optimization via Constrained Confidence Regions , 1996 .

[10]  Elsayed A. Elsayed,et al.  Optimal levels of process parameters for products with multiple characteristics , 1993 .

[11]  R. H. Myers,et al.  Response Surface Techniques for Dual Response Systems , 1973 .

[12]  Shing I. Chang,et al.  A MULTIPLE-OBJECTIVE DECISIONMAKING APPROACH FOR ASSESSING SIMULTANEOUS IMPROVEMENT IN DIE LIFE AND CASTING QUALITY IN A DIE CASTING PROCESS , 1994 .

[13]  Kwok-Leung Tsui,et al.  Economical experimentation methods for robust design , 1991 .

[14]  George E. P. Box,et al.  Dispersion Effects From Fractional Designs , 1986 .

[15]  Joseph J. Pignatiello,et al.  STRATEGIES FOR ROBUST MULTIRESPONSE QUALITY ENGINEERING , 1993 .

[16]  Thomas L. Saaty,et al.  Multicriteria Decision Making: The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation , 1990 .

[17]  Leon S. Lasdon,et al.  Design and Testing of a Generalized Reduced Gradient Code for Nonlinear Programming , 1978, TOMS.

[18]  R. H. Myers,et al.  Response Surface Methodology: Process and Product Optimization Using Designed Experiments , 1995 .

[19]  Bong-Jin Yum,et al.  On parameter design optimization procedures , 1991 .

[20]  Dennis K. J. Lin,et al.  Dual Response Surface Optimization: A Fuzzy Modeling Approach , 1998 .

[21]  William T. Scherer,et al.  "The desirability function: underlying assumptions and application implications" , 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

[22]  D. Ruppert,et al.  Transformation and Weighting in Regression , 1988 .

[23]  Louis Cohen,et al.  Quality Function Deployment: How to Make QFD Work for You , 1995 .

[24]  Douglas C. Montgomery,et al.  Modified Desirability Functions for Multiple Response Optimization , 1996 .

[25]  D. Kendall,et al.  The Statistical Analysis of Variance‐Heterogeneity and the Logarithmic Transformation , 1946 .

[26]  G. Geoffrey Vining A Compromise Approach to Multiresponse Optimization , 1998 .

[27]  J. E. Freund,et al.  Modern Elementary Statistics , 1968 .

[28]  Jeanine Weekes Schroer,et al.  The Finite String Newsletter Abstracts of Current Literature Glisp User's Manual , 2022 .

[29]  Elsayed A. Elsayed,et al.  A case study on process optimization using the gradient loss function , 1995 .

[30]  Yoji Akao,et al.  Quality Function Deployment : Integrating Customer Requirements into Product Design , 1990 .

[31]  W. Biles A Response Surface Method for Experimental Optimization of Multi-Response Processes , 1975 .

[32]  C. Ireland Fundamental concepts in the design of experiments , 1964 .

[33]  Peter R. Nelson,et al.  Design and Analysis of Experiments, 3rd Ed. , 1991 .

[34]  J. E. Freund,et al.  Modern elementary statistics , 1953 .

[35]  Leonie Kohl,et al.  Fundamental Concepts in the Design of Experiments , 2000 .

[36]  Don Gunther,et al.  Quality Function Deployment - How to Make QFD Work for You , 2000 .

[37]  John H. Sheesley,et al.  Quality Engineering in Production Systems , 1988 .

[38]  Noel Artiles-León,et al.  A Pragmatic Approach to Multiple-Response Problems Using Loss Functions , 1996 .

[39]  Susan L. Albin,et al.  A HIERARCHICAL APPROACH TO OPTIMIZING DESCRIPTIVE ANALYSIS MULTIRESPONSE EXPERIMENTS , 1999 .

[40]  R. H. Myers,et al.  Response Surface Alternatives to the Taguchi Robust Parameter Design Approach , 1992 .

[41]  Raghu N. Kacker,et al.  Performance measures independent of adjustment , 1987 .

[42]  N. Logothetis,et al.  Characterizing and optimizing multi‐response processes by the taguchi method , 1988 .

[43]  Douglas C. Montgomery,et al.  Response Surface Methodology: Process and Product Optimization Using Designed Experiments , 1995 .

[44]  Marjorie Leeson,et al.  Fundamental Concepts , 1985, Operator-Adapted Wavelets, Fast Solvers, and Numerical Homogenization.